Selective underascertainment of cases may bias estimates of cancer patient survival. We show that the magnitude of potential bias strongly depends on the time periods affected by underascertainment and on the type of survival analysis (cohort analysis vs period analysis). We outline strategies on how to minimise or overcome potential biases. Population-based monitoring of cancer patient survival is an important task of cancer registries (e.g. Berrino et al, 1995Berrino et al, , 1999Berrino et al, , 2003Dickman et al, 1999;Talbäck et al, 2003). As with other cancer statistics, the validity of population-based cancer survival estimates depends on the quality of the cancer registry data. Most obviously, a minimum requirement is reliable follow-up of patients with respect to vital status. The validity of survival estimates may also depend on completeness of cancer registration (Monnet et al, 1998;Prior et al, 1998). In particular, selective underascertainment of patients with a good prognosis may lead to underestimation of cancer patient survival, whereas an opposite effect could result from selective underascertainment of patients with poor prognosis. The aim of this paper is to assess the impact of various patterns of incompleteness of cancer registration on population-based estimates of cancer patient survival in a quantitative manner.
MATERIAL AND METHODS DatabaseOur analysis is based on data from the nationwide Finnish Cancer Registry whose true completeness (in terms of ascertainment of both incident cases and follow-up status) is known to be very close to 100% (Teppo et al, 1994). We included patients, aged 15 years or older, with a first diagnosis of one of the six most common forms of cancer in Finland between 1990 and 1999.
Statistical analysisThe impact of underascertainment of incident cases was assessed for 5-year relative survival rates (Ederer et al, 1961), which were derived using Hakulinen's (1982) method by two different approaches illustrated in Figure 1. With the first approach, 5-year survival rates were calculated for the cohort of patients diagnosed in 1990 -1994 and followed with respect to vital status until the end of 1999 (solid frame). The second approach is the so-called period analysis, which has first been proposed a few years ago to provide more up-to-date estimates of cancer patient survival Gefeller 1996, 1997). Here, 5-year relative survival estimates for the 1995 -1999 period are reported, which exclusively reflect the survival experience of patients during those years (dashed frame).To assess the impact of incompleteness of registration either in the earlier or in the more recent years of the database, we carried out both a cohort analysis for the 1990 -1994 cohort and a period analysis for the 1995 -1999 period, assuming underascertainment of the following cases either in 1990 -1994 or in 1995 -1999 in different scenarios: (a) all cases, (b) only cases dying within 5 years following diagnosis and (c) only cases still alive 5 years following diagnosis.Expected survival estimate...